communication compression

Catalyst Acceleration of Error Compensated Methods Leads to Better Communication Complexity AISTATS 2023 CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks ICML 2023 Communication-Efficient Stochastic Gradient Descent Ascent with Momentum Algorithms IJCAI 2023 Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data ICML 2023 DASHA: Distributed Nonconvex Optimization with Communication Compression and Optimal Oracle Complexity ICLR 2023 FedLab: A Flexible Federated Learning Framework JMLR 2023 Momentum Provably Improves Error Feedback! NeurIPS 2023 On Biased Compression for Distributed Learning JMLR 2023 Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation NeurIPS 2023 Private Federated Learning with Autotuned Compression ICML 2023 Unbiased Compression Saves Communication in Distributed Optimization: When and How Much? NeurIPS 2023 Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top ICLR 2023 Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning AISTATS 2022 BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression NeurIPS 2022 Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox NeurIPS 2022 Communication-Compressed Adaptive Gradient Method for Distributed Nonconvex Optimization AISTATS 2022 Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data ICML 2022 Correlated Quantization for Distributed Mean Estimation and Optimization ICML 2022 DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning ICML 2022 Distributed Online Convex Optimization with Compressed Communication NeurIPS 2022 Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees NeurIPS 2022 Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression NeurIPS 2022 Permutation Compressors for Provably Faster Distributed Nonconvex Optimization ICLR 2022 QSFL: A Two-Level Uplink Communication Optimization Framework for Federated Learning ICML 2022 SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression NeurIPS 2022